Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add yarlson/yarstack --skill crap-index-assessgit clone --depth 1 https://github.com/yarlson/yarstackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yarlson/yarstack/crap-index-assess)<a href="https://agentmods.dev/skills/yarlson/yarstack/crap-index-assess"><img src="https://agentmods.dev/badge/skills/yarlson/yarstack/crap-index-assess/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yarlson/yarstack/crap-index-assess"><img src="https://agentmods.dev/badge/skills/yarlson/yarstack/crap-index-assess.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00077 | $0.00994 |
| Opus 5.5 | $0.00031 | $0.00398 |
| Sonnet 5.5 | $0.00015 | $0.00199 |
| Haiku 4.5 | $0.00008 | $0.00099 |
Grade A, and why
crap-index-assess scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRAP Index Assessment
Use the CRAP index as a method-level risk signal, not as a verdict on code quality or a target to game.
Measure
- Confirm the source revision and the methods in scope.
- Read repository instructions, command entrypoints, scripts, manifests, analysis configuration, and CI needed to find an existing CRAP measurement and its documented prerequisites.
- When the repository configures a CRAP command, run that command with its existing defaults and any documented project-native prerequisite that produces its coverage input. Preserve its complexity and coverage definitions, exclusions, precision, aggregation, and configured threshold. Do not replace it with an ad hoc command, install a tool, or change its configuration.
- If the configured command fails, report the command and failure. Do not use partial or stale output. Use a manual fallback only when reliable method-level complexity and coverage from the same revision remain available, and label the result as a fallback rather than a successful tool run.
- Use the manual calculation only when the repository has no configured CRAP measurement or the preceding fallback condition applies.
Manual Calculation
-
Record how the available measurement defines cyclomatic complexity and coverage. Treat complexity as one plus the decisions in a method unless the measurement defines it differently. Prefer branch or basis-path coverage from automated, repeatable tests; when only another coverage type is available, name it and state the limit.
-
Validate cyclomatic complexity
c >= 1and coverage percentage0 <= cov <= 100. Do not estimate missing values, mix incompatible reports, or substitute class averages for method data. -
Calculate uncovered proportion
u = 1 - cov / 100, then calculate:CRAP(m) = c² × u³ + c -
Show the inputs and substituted calculation with enough precision to reproduce the result. At full coverage the score equals complexity; at zero coverage it equals
c² + c. -
Rank methods by score. State the chosen boundary:
> 30is a common fallback, while some definitions and tools use>= 30. Do not hide the boundary choice. For a larger scope, report the count and percentage of methods beyond it as well as the highest-risk methods; an average alone can hide hotspots.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago Changed 65bfb7a71e74
- 1mo ago First seen · 53 lines · 77 tokens per session scan A 3c78cda32553
crap-index-assess is a skill published in the GitHub repository yarlson/yarstack (3 stars, last pushed 6d ago), licensed MIT. It adds 77 tokens to every session and 994 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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